Figure REF  shows
qualitative comparison of CenterMask [1]} and BCNet on images with overlapping objects. In each ROI region, GCN-1 detects occluding regions while GCN-2 models the partially occluded instance by directly regressing the contours and masks. For example, BCNet decouples the occluding and occluded baseball players in similar clothes into GCN-1 and GCN-2 respectively, and detects the left leg missed by CenterMask. See supplementary file for more visual comparisons.
